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Panga Interdiction Predictive Model
Risk/Behavior Based Model for Maritime Interdictions SummaryMaritime drug/migrant smugglers using pangas (custom fishing boats constructed in Mexico) present a pressing and increasingly hostile homeland security threat in California, as evidenced by the year- over-year increase in activity, and by the December 2012 murder of United States Coast Guard Chief Petty Officer Horne. This project will develop a predictive analytic maritime interdiction model for the United States Coast Guard, Customs and Border Protection Marine, United States Border Patrol, California National Guard, and local law enforcement personnel; the model will provide a timely prediction of when/where maritime migrant and drug smugglers might transit from Mexico into US waters off the coast of California. If fully funded, a web-based tool would be created from the model; the tool would allow law enforcement stakeholders the ability to predict where maritime
drug/migrant smugglers may be operating off of the Southern California coast, allowing more efficient allocation of enforcement resources, and the possibility of a higher number of maritime smuggler interdictions. The tool would build upon the Port Resilience
Operational/Tactical Enforcement to Combat Terrorism (PROTECT) model’s algorithms and United States Coast Guard execution of the model to build enhanced marine domain awareness, outside of the country’s ports and harbors.
1. Theme Area: Risk Management/Operations Research 2. Principal Investigator: Dr. Lance Larson
3. Institution: San Diego State University 4. Co-Investigators: Dr. Michael Orosz (University of Southern California); Alex Carrillo (Lieutenant Commander Sel., USCG Reserve), Dr. Robert Nolker (Analyze Corporation), Scott G. Chase (Analyze Corporation)
5. Research Transition Lead: Dr. Michael Orosz (USC)
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6. Keywords: Risk modeling, maritime,
smuggling, transnational crime, predictive analytics, law enforcement, mathematical programming, machine learning
7. Brief Description:
The purpose of this research is to produce a predictive, tactical interdiction model (and resultant tool) which would reduce operational risk, and patrol asset costs to the US Coast Guard (USCG), US Border Patrol (USBP), Customs and Border Protection Marine (CBP-M), California National Guard and local law enforcement charged with conducting maritime counter-smuggling patrols in California. The model would enhance the ability of the agencies to predict when/where maritime smugglers would bring migrant/drug loads to the California coast, thereby enhancing patrol effectiveness and reducing the costs of human and patrol asset resources. The model would build off previous work by Mr. Carrillo, and utilize inputs of signature/previous smuggler activity, weather/sea state information, and available “blue force” (law enforcement) resources. If fully funded, a
working, web-based tool would be given to the law enforcement stakeholders; the tool would allow those agencies to best plan plans in the maritime, landside and air domains; those patrols would have
a higher likelihood of interdicting migrant/drug-laden pangas off the coast of Southern California waters.
8. Research Objectives:
This research will: (a) produce a predictive model that will inform USCG, CBP Marine, US Border Patrol, and local law enforcement personnel when and where to perform maritime and landside law enforcement patrols; (b) determine the factors and pattern behavior of maritime smugglers in California; (c) determine the likely detection success rate for law enforcement agencies using the predictive maritime smuggling model; (d) determine the likely, associated cost savings to the law enforcement agencies using the predictive model; (e) determine likely smuggler behavior, in response to law enforcement actions which were guided by the predictive model.
9. Research Transition Objectives:
If partially funded, the project will develop a predictive analytic model for maritime
smuggling in Southern California; the aim of the predictive analytic model is to best predict when/where smugglers may operate. The predictive ability of the model will be tested, and compared against current and on-going maritime smuggler activity in Southern California. If fully funded, the project will build upon the predictive analytic maritime model, and the success and execution of USC’s Port Resilience Operational/Tactical Enforcement to Combat Terrorism (PROTECT) model to transition predictive research into a useable interdiction tool for the law enforcement operator/planner. The web-based tool’s predictive analytics will be tested against real, continuing maritime smuggler activity in Southern California, to measure the tool’s effectiveness.
Page 3 of 8 10. Interfaces to CREATE Projects:
The goal of the Panga Interdiction Predictive Model is to build upon two previous University of Southern California (USC) maritime projects, and build greater Maritime Domain Awareness (MDA). Such previous projects include the Port Resilience Operational/Tactical Enforcement to Combat Terrorism (PROTECT) model, and PortSec: Port Operations Modeling for Risk Management and Resource Allocation. Dr. Orosz will use his recent research on PortSec to help formulize the Panga Interdiction Predictive Model’s algorithms, and risk/decision making. Further, through the associates of LCDR (sel.) Carrillo and Dr. Orosz, project members will work with the USCG, and PROTECT model team to model defender/attacker scenarios and use team’s experiences
with model implementation and execution with USCG.
11. Previous or current work relevant to the proposed project.
In addition to Dr. Orosz’s work previous PortSec work, Mr. Carrillo recently produced a cursory predictive model for panga predictions while working on coursework with the University
California Irvine’s Predictive Analysis program; Mr. Carrillo was able to determine that there is predictive ability involving ocean sea state and moon phase, and presented his findings at the 2014 Maritime Intelligence Fusion Center Pacific (MIFC-PAC) Intelligence Symposium and the 5th Annual Maritime Risk at USC.
Additionally, Analyze Corporation (Dr. Nolker and Mr. Chase) was recently recognized in Wired Magazine (article in references) for their work in mapping illegal fishing using spaced-based AIS. Dr. Robert Nolker specifically completed a predictive project involving “Fishing Behavior on the High Seas Using Ship Position and Time data to Determine Geospatial Behavior Analytics.” By observing long-term vessel movement patterns of all the ships on the ocean Dr. Nolker and Mr. Chase employed a feature reduction and statistical behavior
classification-based approach. Through
this technique, Analyze Corporation was able to make automated determinations as to whether a ship is engaged in fishing, as distinct from other maritime activities such as cargo transiting, passenger service, tug and rescue activity and maritime law enforcement. These algorithms have been incorporated into the IUU fishing work of globalfishingwatch.org backed by Oceana, Google and Skytruth. The algorithms are also being used by Spacequest to deliver a real-time vessel activity viewer.
12. Major Research Transition Products and Customers:
Project deliverables will consist of: (a) a working tool that will allow USCG, CBP-M, USBP, and California National Guard to continually plan maritime and landside counter-smuggling patrols in California (fully-funded project); (b) a predictive model that will show USCG, CBP-M, USBP, and California National Guard how maritime smuggler activity in Southern California could be predicted (partially-funded project); (c) report to all stakeholder detailing the impact of the model on risk, and the effectiveness/confidence of the predictors used in the model and (d) a cost benefit analysis to the primary stakeholders on the model implementation cost, compared to potential cost savings from predictive patrol asset implementation.
Page 4 of 8 13. Technical Approach:
The technical approach would first focus on studying the application of previous
maritime/security risk algorithms developed by USC and the “signature based behavior analysis” Analyze Corporation conducted (Fishing behavior model), and incorporate the “Boosted Trees” panga analysis of Mr. Carrillo. The model would then conduct consequence/risk assessment models, risk reduction assessments and predictive analysis models based on a mix of
methodologies including probabilistic risk analysis and qualitative assessments by modeling and maritime experts, as appropriate.
Dr. Nolker and Mr. Chase’s approach defines communities, users, or groups of individuals based on their characteristics in order to then use the data to establish behavior signatures used to highlight a desired behavior. Stated simply, rather than depending on a specialized individual’s knowledge of criminal behavior within a domain (which criminals often go to great lengths to conceal), Analyze uses behavior patterns in a data set to identify the desired behavior. The concept is called “signature based behavioral analysis.”
Signature based behavioral analysis is an analytical approach to defining a nominal behavior of a group or class by deriving a signature from the characteristic data for that group or class. The signature is built using social network analysis, structure mining, and weighting algorithms. All the data characteristics are put through a process involving machine learning and link analysis to identify key structures in the data set. This structure is then mined and weighted to produce a signature. By using the characteristics of available domain data the signature will morph over time as data within set changes. Signatures for maritime smuggler activity would be created for the various patterns of activity exhibited by maritime smugglers operating in Southern California. Phase I – Panga Prediction Model
In the first phase, the maritime subject matter expert (Mr. Carrillo) will outline the smuggling factors that impact the “attacker” side of the model, whereby the project would define under what parameters a Mexican maritime smuggler may decide to conduct a smuggling operation, and what “defender” (law enforcement) actions may preclude such a smuggler from completing a maritime smuggling evolution. Mr. Carillo will work closely and interact with the USCG (Dr. Joe DiRenzo and Mr. David Boyd) throughout the conduct of this work. Relevant data will be given to test the hypotheses of the variables that impact the “attacker”/”defender” predictive model, to include data on previous smuggling events. Information assumptions will be tested against previously experienced smuggling events in order to determine what is the mix of factors, and with what level of predictability, that determine if/when smugglers ship narcotics from Mexico to Southern California via maritime corridors. The product of this research will be a working model that determines the factors and predictability of maritime smuggling in Southern California.
Phase II – Panga Prediction Tool
If funded, the second phase will turn the panga prediction model developed in Phase I into a working tool for law enforcement to plan maritime, land, and air law enforcement asset patrols. The intent of the tool is to allow operational law enforcement planners the ability to use
historical (previous smuggling information and circumstances) and forecasted conditions (to include weather sea state) to determine the likelihood of a smuggling event, and better assign patrol assets to areas that will allow for greater smuggler detection/apprehension rates. The
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research team will maintain their close working relationship and interaction with the USCG (Dr. Joe DiRenzo and Mr. David Boyd) throughout the conduct of this work.
In the second phase, mathematicians and programmer will use the model from Phase I to build a computer accessible program that will use attacker/defender inputs to predict smuggler activity.
14. References:
(1) Orosz, Michael, Anthony Barrett, and Petros Loannou. PortSec: Port Operations
Modeling for Risk Management and Resource Allocation.
(2) Analyze Corporation. Fishing Behavior on the High Seas Using Ship Position and Time
Data to Determine Geospatial Behavior Analytics. 2014.
(3) Gibbs, Wayt. "The Plan to Map Illegal Fishing from Space | WIRED." Wired.com. Conde Nast Digital, 11 Nov. 0014. Web. 01 Dec. 2014.
15. Major Milestones and Dates:
**
Phase I Major Milestones Date
1. Complete benchmark and determine relevant previous algorithms from Analyze
Corporation, USC PortSec and other, related maritime projects
15 August 2015 2. Aggregate and clean existing panga interdiction and variable data 31 October 2015 3. Develop and test panga prediction model 15 December
2015
Phase II Major Milestones Date
4. Test and enhance tool predictions against experienced smuggling activity 15 January 2016 5. Implement and test panga prediction model into a user-friendly, accessible
tool
31 March 2016 6. Explore improvements of model/tool to account for continuous “attacker”
procedure changes
15 April 2016 7. Determine and present cost benefit analysis of the panga prediction
model/tool
15 May 2016 7. Prepare presentation for CREATE/industry/academic presentations 01 June 2016
16. Brief Bios:
Michael Orosz, Ph.D. (Lead, Decision Systems Group, University of Southern California) - Dr. Michael Orosz has over 29 years experience in commercial and government software development, basic and applied research and development, project management, academic research, and has developed and deployed several commercially successful products. His research interests include decision systems, predictive analysis, integrated modeling environments, distributed system of systems, operational risk
management and intelligence human-computer interfaces.
Dr. Orosz has successfully led projects in developing command and control, intelligence analysis and model-based decision-support systems for applications ranging from protecting the Nation’s
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food supply, ensuring maritime and sea port security, protecting the Nation’s infrastructures and cities against terrorism events and enhanced C2I technologies used in the Intelligence Community. Dr. Orosz is a principal investigator at the DHS National Center for Risk and Economic Analysis of Terrorism Events (CREATE) where he leads the development of InfraSec–an infrastructure terrorism risk assessment and security resource allocation system currently focused on large spectator venues such as sport stadiums, PortSec–a seaport infrastructure version of InfraSec currently focused on Ports of Los Angeles/Long Beach operations and iSARs–a suspicious activity reporting intelligence and decision analysis system. He is also a principal investigator at the DHS National Center for Food Protection Defense (NCFPD) and the DHS National Center for Foreign Animal and Zoonotic Diseases (FAZD). He recently served (2006-2009) as the Information Analytics Science Leader and member of the
executive committee for the FAZD Center. In addition, Dr. Orosz has recently or is presently managing projects funded by DARPA, DHS, DOE, IARPA, NASA, NRO, NSA, ONR, and the USMC.
Dr. Orosz received a B.S. in Engineering from the Colorado School of Mines, a M.S. in
Computer Science from the University of Colorado, and a Ph.D. in Computer Science from the University of California at Los Angeles. Prior to joining USC, Dr. Orosz worked in the
aerospace/defense, motion picture entertainment, engineering consulting, and heavy-mining (natural resources) industries.
Lance Larson, Ph.D. (Assistant Director, San Diego State University, Graduate Program in Homeland Security Program) - Lance W. Larson is the Assistant Director of San Diego State’s Homeland Security Program. In addition, Dr. Larson is the President and CEO of Larson Corporation -- a consulting firm offering both information security and information systems development consulting. Dr. Larson has founded and sold several successful businesses. The last of which, a website hosting and secure network operations center, was valued at nearly $2 million in just 4 years of operation, and operated with zero debt.
Dr. Larson's business and security expertise draws from experience working with
counterterrorism training at the FBI Laboratory (Quantico, VA), and his assignment to a law enforcement intelligence and Department of Homeland Security sponsored Fusion Center Task Force, with emphasis in cyber security. Dr. Larson has also helped coordinate homeland security and Department of Defense exercises for federal, state, and municipal governments.
Dr. Larson holds an active government security clearance. Lance has also authored two books on entrepreneurship and business information assurance and physical security. Dr. Larson received his Master of Science degree (Interdisciplinary Studies -- Homeland Security) from San Diego State University. He was awarded his Ph.D. in Applied
Management and Decision Science with a focus on Information System Management in 2009 from Walden University. Continually striving for self-improvement, Dr. Larson is a Certified Information Systems Security Professional (CISSP), certified as a CompTIA Inet+ Subject Matter Expert, and holds many other certifications related to homeland security and information technology. Dr. Larson was a 2001 NACE (GSEA) entrepreneur award finalist in Washington, D.C., a 2002 California Office of the Attorney General, Distinguished Citizen, and SDSU Favorite Faculty nominee 2012, 2013 and 2014
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Additionally, Dr. Larson has volunteered as a Reserve Police Officer for a law enforcement agency in Orange County, CA since 2001. In such capacity he assists a team of law
enforcement experts in fighting Internet crime. Among his many awards and distinctions are medals of lifesaving, merit, and valor during his tenure with the police department.
Dr. Larson's areas of research include cyber security, security convergence theory, vulnerabilities of fiber-optic networks, cyber threat analysis, homeland security, network security, systems theory and information assurance.
Dr. Larson's professional affiliations include membership in ISACA (Information Systems Audit and Control Association), CRPOA (California Reserve Peace Officers Association), EO (Entrepreneurs' Organization), and an Honorary Lifetime Faculty Brother, Alpha Kappa Psi.
Alexander P. Carrillo. (Lieutenant Commander Sel., United States Coast Guard Reserve) - Alex Carrillo was commissioned as an officer at the U.S. Coast Guard Academy in 2004, after graduating with a B.S. in Management. LT Carrillo then served as Deck Watch Officer, Boarding Officer, Maritime Mission Commander, Intelligence Officer and Gunnery Officer aboard the USCGC CHASE (WHEC-718). Upon completion of his tour, he received the USCG Achievement Medal for the successful prosecution of a 40’ go-fast drug vessel carrying $98M in cocaine off the coast of Ecuador.
In 2006, LT Carrillo was assigned as the Assistant Supervisor of the Field Intelligence Support Team in San Diego, and was in charge of counter-migrant/narcotic intelligence collections. He was later promoted to Lieutenant, and was nominated the Area Maritime Security Committee Intelligence Subcommittee Chairman. In that position, he guided the strategic intelligence coordination of 15 federal and state agencies, and was awarded the USCG Commendation Medal.
In 2009, Alex joined the USCG reserve as an intelligence officer at the Maritime Intelligence Fusion Center Pacific, where he focused on geopolitical issues. He concurrently worked as a contract intelligence analyst at the San Diego Law Enforcement Coordination Center, where he was responsible for strategic analysis of terrorism tips and leads, and liaising with the FBI Joint Terrorism Task Force.
In April 2011, Alex joined the Orange County Intelligence Assessment Center as an intelligence analyst, and also serves as President of the San Diego Chapter of the
Association for Intelligence Officers. Alex holds a M.S. in Quality Systems Management, and is currently pursuing predictive analytic models to address maritime smuggling problems through the University of California, Irvine.
Robert Nolker, Ph.D. (Vice President of Research and Development at Analyze Corporation) - Dr. Nolker brings more than 10 years of practical application of data
science from academia and the intelligence communities. Most recently, Dr. Nolker was part of an elite team that conducted cyber vulnerability assessments using advanced data science techniques. He is best known for his development of behavioral algorithms for new analyst support tools used by the intelligence community for human resource targeting, and he is currently developing behavioral algorithms using satellite based data for ocean asset
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monitoring. He is distinguished in Academia for pioneering new advanced techniques for conducting social network analysis. Dr. Nolker received his Master’s degree and Ph.D. in Information Systems from the University of Maryland Baltimore County and prior to that operated and sold a mid-sized management-consulting firm focused on process optimization.
Scott G. Chase (Chief Technologist at Analyze Corporation) - With more than ten years of experience in software security assessment, computer network operations, and cyber warfare,
Mr. Chase’s book, The Software Vulnerability Guide, has become a hallmark of training for
cyber security training. Prior to co-founding Analyze, Mr. Chase was an Engineering Fellow at Raytheon, managing a cross-company R&D team focused on next- generation cyber security products, participation in due diligence and transition planning for cyber security acquisitions, leading workforce development and training initiatives for cyber and preparing for the launch of the company’s external cyber training business. In 2008, SI Government Solutions, the company that Mr. Chase grew from 5 to 35 cyber security professionals, was acquired by Raytheon. Mr. Chase graduated in Computer Science with Honors from the Florida Institute of Technology. Mr. Chase is Analyze's Chief Technology Officer.
